Feature Selection In Acquiring The Significant Features For Writer Identification

Azah Kamilah, Muda and Yun Huoy, Choo and Ummi Rabaah, Hashim (2011) Feature Selection In Acquiring The Significant Features For Writer Identification. Project Report. UTeM, Melaka, Malaysia. (Submitted)

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Abstract

Handwriting is individualistic. The uniqueness of shape and style of handwriting can be used to identify the significant features in authenticating the author of writing. The main issue in Writer Identification (WI) domain is how to acquire these significant features that reflect the author of handwriting. WI is an active area of research in pattern recognition due to extensive exchange of paper documents. This research is meant to explore the usage of feature selection in WI. The purpose of feature selection is to obtain the most minimal sized subset of features which class distribution is as close as possible to original class distribution. The three popular methods of feature selection are filter method, wrapper method, and embedded method, however only wrapper method will be further explored in this research. This research focuses on identifying the significant features of word shape by using wrapper feature selection method prior the identification task. Feature selection is explored in order to find the most significant features which by is the unique features of individual's writing. This research also proposes an improved Sequential Forward Floating Selection method besides the exploration of significant features for invarianceness of authorship from global shape features by using various wrapper feature selection methods. The promising results show that the proposed method is worth to receive further exploration in identifying the handwritten authorship.

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